scholarly journals Daily Microwave-Derived Surface Temperature over Canada/Alaska

2007 ◽  
Vol 46 (5) ◽  
pp. 591-604 ◽  
Author(s):  
A. Mialon ◽  
A. Royer ◽  
M. Fily ◽  
G. Picard

Abstract The land surface temperature variation over northern high latitudes in response to the increase in greenhouse gases is challenging because of the lack of meteorological stations. A new method to derive the surface temperature from satellite microwave measurements that improves the frequency of measurements relative to that of infrared data is presented. The daily Special Sensor Microwave Imager 25 km × 25 km Equal-Area Scalable Earth Grid (EASE-Grid) dataset provided by the National Snow and Ice Data Center in Boulder, Colorado, is processed to derive the surface temperature using the method proposed by Fily et al. A normalization approach based on the 40-yr ECMWF reanalysis (ERA-40; 2.5°) temperature diurnal cycle fitted for each pixel is applied to overcome the time acquisition variation of measurements as well as to interpolate missing data. An adaptive mask for discriminating between ice-free pixels and snow-free pixels is also applied. The resulting database is thus a new consistent hourly series of near-surface air temperatures during the summer (without snow). The mean accuracy is on the order of 2.5–3 K when compared with the synchronous in situ air temperature and different gridded datasets over Canada and Alaska. The trend over the last 10 yr confirms observed climate evolution: an increase in summer surface temperature of +0.09° ± 0.04°C yr−1, at the 90% confidence level, for Canada between 1992 and 2002, whereas a decrease of −0.15° ± 0.05°C yr−1, at the 95% confidence level, is observed for Alaska. Spatial and temporal anomalies show regional impacts of meteorological phenomena such as the El Niño extreme warm summer episode of 1998, the decrease in temperatures in 1992 in Canada following the volcanic eruption of Mount Pinatubo in June 1991, and the strong drought in the prairies in 2001. The annual sum of positive degree-days (thawing index) has been related to the permafrost distribution. The lower values of the derived thawing index (<1400 degree-days) are related well to the presence of continuous and dense discontinuous permafrost. The observed increase in the thawing index during the 1992–2002 period represents a decrease of classified permafrost area of 7%.

Author(s):  
Elizabeth Good

The behaviour of remotely sensed land surface temperatures (LSTs) from the spinning-enhanced visible and infrared imager (SEVIRI) during the total solar eclipse of 20 March 2015 is analysed over Europe. LST is found to drop by up to several degrees Celcius during the eclipse, with the minimum LST occurring just after the eclipse mid-point (median=+1.5 min). The drop in LST is typically larger than the drop in near-surface air temperatures reported elsewhere, and correlates with solar obscuration ( r =−0.47; larger obscuration = larger LST drop), eclipse duration ( r =−0.62; longer duration = larger LST drop) and time ( r =+0.37; earlier eclipse = larger LST drop). Locally, the LST drop is also correlated with vegetation (up to r =+0.6), with smaller LST drops occurring over more vegetated surfaces. The LSTs at locations near the coast and at higher elevation are also less affected by the eclipse. This study covers the largest area and uses the most observations of eclipse-induced surface temperature drops to date, and is the first full characterization of satellite LST during an eclipse (known to the author). The methods described could be applied to Geostationary Operational Environmental Satellite (GOES) LST data over North America during the August 2017 total solar eclipse. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’.


2004 ◽  
Vol 41 (12) ◽  
pp. 1437-1451 ◽  
Author(s):  
K C Karunaratne ◽  
C R Burn

The association of site characteristics with the n-factor, a ratio of air to ground surface temperature, was investigated at five sites in the boreal forest near Mayo, Yukon Territory. Permafrost was in equilibrium with surface conditions at three sites, was degrading at another, and was absent from the fifth. Air and near-surface ground temperatures were recorded by data loggers between September 2000 and April 2002, and mean daily temperatures were accumulated to calculate n-factors for the freezing (nf) and thawing (nt) seasons. Air temperature did not vary between the sites, so inter-site differences in nf and nt were because of variations in surface temperature. Variations in nf between the sites over the two winters were primarily because of differences in snow depth, but at sites with similar snow cover, the surface temperatures were relatively high when the site was underlain by unfrozen ground. During summer, daily mean surface temperatures were initially less than air temperatures. However, once the thawing front had penetrated below the depth of diurnal temperature fluctuation, the air and ground surface temperatures converged. Since the rate of thaw penetration is governed by soil thermal diffusivity, nt varies directly with this property. These results indicate that subsurface conditions, particularly absolute temperature and ground thermal properties, exert considerable influence on n-factors, and, at the Mayo sites, the influence is greater than that of the vegetation.


2019 ◽  
Vol 12 (3) ◽  
pp. 1531-1543 ◽  
Author(s):  
Samuel Favrichon ◽  
Catherine Prigent ◽  
Carlos Jimenez ◽  
Filipe Aires

Abstract. Remotely sensed brightness temperatures from passive observations in the microwave (MW) range are used to retrieve various geophysical parameters, e.g. near-surface temperature. Cloud contamination, although less of an issue at MW than at visible to infrared wavelengths, may adversely affect retrieval quality, particularly in the presence of strong cloud formation (convective towers) or precipitation. To limit errors associated with cloud contamination, we present an index derived from stand-alone MW brightness temperature observations, which measure the probability of residual cloud contamination. The method uses a statistical neural network model trained with the Global Precipitation Microwave Imager (GMI) observations and a cloud classification from Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI). This index is available over land and ocean and is developed for multiple frequency ranges to be applicable to successive generations of MW imagers. The index confidence increases with the number of available frequencies and performs better over the ocean, as expected. In all cases, even for the more challenging radiometric signatures over land, the model reaches an accuracy of ≥70 % in detecting contaminated observations. Finally an application of this index is shown that eliminates grid cells unsuitable for land surface temperature estimation.


2011 ◽  
Vol 5 (3) ◽  
pp. 1547-1582
Author(s):  
S. Gruber

Abstract. Permafrost underlies much of Earths' surface and interacts with climate, eco-systems and human systems. It is a complex phenomenon controlled by climate and (sub-) surface properties and reacts to change with variable delay. Heterogeneity and sparse data challenge the modeling of its spatial distribution. Currently, there is no data set to adequately inform global studies of permafrost. The available data set for the Northern Hemisphere is frequently used for model evaluation, but its quality and consistency are difficult to assess. A global model of permafrost extent and dataset of permafrost zonation are presented and discussed, extending earlier studies by including the Southern Hemisphere, by consistent data and methods, and most importantly, by attention to uncertainty and scaling. Established relationships between air temperature and the occurrence of permafrost are re-formulated into a model that is parametrized using published estimates. It is run with a high-resolution (<1 km) global elevation data and air temperatures based on the NCAR-NCEP reanalysis and CRU TS 2.0. The resulting data provides more spatial detail and a consistent extrapolation to remote regions, while aggregated values resemble previous studies. The estimated uncertainties affect regional patterns and aggregate number, but provide interesting insight. The permafrost area, i.e. the actual surface area underlain by permafrost, north of 60° S is estimated to be 13–18 × 106 km2 or 9–14 % of the exposed land surface. The global permafrost area including Antarctic and sub-sea permafrost is estimated to be 16–21 × 106 km2. The global permafrost region, i.e. the exposed land surface below which some permafrost can be expected, is estimated to be 22 ± 3 × 106 km2. A large proportion of this exhibits considerable topography and spatially-discontinuous permafrost, underscoring the importance of attention to scaling issues and heterogeneity in large-area models.


2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.


2020 ◽  
Vol 242 ◽  
pp. 111746 ◽  
Author(s):  
Mohammad Karimi Firozjaei ◽  
Solmaz Fathololoumi ◽  
Seyed Kazem Alavipanah ◽  
Majid Kiavarz ◽  
Ali Reza Vaezi ◽  
...  

2017 ◽  
Vol 145 (12) ◽  
pp. 4727-4745 ◽  
Author(s):  
Elena Tomasi ◽  
Lorenzo Giovannini ◽  
Dino Zardi ◽  
Massimiliano de Franceschi

The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions in a typical Alpine valley. Accordingly, model results are compared against data collected during an intensive field campaign performed in the Adige Valley, in the eastern Italian Alps. In particular, the ability of the model in reproducing the time evolution of 2-m temperature and of incoming and outgoing shortwave and longwave radiation is examined. The validation of model results highlights that, in this context, WRF reproduces rather poorly near-surface temperature over snow-covered terrain, with an evident underestimation, during both daytime and nighttime. Furthermore it fails to capture specific atmospheric processes, such as the temporal evolution of the ground-based thermal inversion. The main cause of these errors lies in the miscalculation of the mean gridcell albedo, resulting in an inaccurate estimate of the reflected solar radiation calculated by both Noah and Noah_MP. Therefore, modifications to the initialization, to the land-use classification, and to both land surface models are performed to improve model results, by intervening in the calculation of the albedo, of the snow cover, and of the surface temperature. Qualitative and quantitative analyses show that, after these changes, a significant improvement in the comparability between model results and observations is achieved. In particular, outgoing shortwave radiation is lowered, 2-m temperature maxima increased accordingly, and ground-based thermal inversions are better captured.


2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.


2020 ◽  
Author(s):  
Zheng Guo ◽  
Miaomiao Cheng

&lt;p&gt;Diurnal temperature range (includes land surface temperature diurnal range and near surface air temperature diurnal range) is an important meteorological parameter, which is a very important factor in the field of the urban thermal environmental. Nowadays, the research of urban thermal environment mainly focused on surface heat island and canopy heat island.&lt;/p&gt;&lt;p&gt;Based on analysis of the current status of city thermal environment. Firstly, a method was proposed to obtain near surface air temperature diurnal range in this study, difference of land surface temperature between day and night were introduced into the improved temperature vegetation index feature space based on remote sensing data. Secondly, compared with the district administrative division, we analyzed the spatial and temporal distribution characteristics of the diurnal range of land surface temperature and near surface air temperature.&lt;/p&gt;&lt;p&gt;The conclusions of this study are as follows:&lt;/p&gt;&lt;p&gt;1 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing were fluctuating upward. The rising trend of the near surface air temperature diurnal range was more significant than land surface temperature diurnal range. In addition, the rise and decline of land surface temperature and near surface air temperature diurnal range in different districts were different. In the six city districts, the land surface temperature and near surface air temperature diurnal range in the six areas of the city were mainly downward. The decline trend of near surface air temperature diurnal range was more significant than land surface temperature diurnal range.&lt;/p&gt;&lt;p&gt;2 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing with similar characteristics in spatial distribution, with higher distribution land surface temperature and near surface air temperature diurnal range in urban area and with lower distribution of land surface temperature and near surface air temperature diurnal range in the Northwest Mountainous area and the area of Miyun reservoir.&lt;/p&gt;


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